Extraneous Variables are undesirable variables that
influence the relationship between the variables that an experimenter
is examining. Another way to think of this, is that these are variables
the influence the outcome of an experiment, though they are not the variables
that are actually of interest. These variables are undesirable because
they add error to an experiment. A major goal in research design is to
decrease or control the influence of extraneous variables as much as possible.

For example, letís say that an educational psychologist
has developed a new learning strategy and is interested in examining the
effectiveness of this strategy. The experimenter randomly assigns students
to two groups. All of the students study text materials on a biology topic
for thirty minutes. One group uses the new strategy and the other uses
a strategy of their choice. Then all students complete a test over the
materials. One obvious confounding variable in this case would be pre-knowledge
of the biology topic that was studied. This variable will most likely
influence student scores, regardless of which strategy they use. Because
of this extraneous variable (and surely others) there will be some spread
within each of the groups. It would be better, of course, if all students
came in with the exact same pre-knowledge. However, the experimenter has
taken an important step to greatly increase the chances that, at least,
the extraneous variable will add error variance equivalently between the
two groups. That is, the experimenter randomly assigned students to the
two groups.

Random assignment is a powerful tool though it does nothing
to decrease the amount of error that occurs as a result of extraneous
variables, in only equalizes it between groups. In fact, even if the experimenter
gave a pre-knowledge test ahead of time and then assigned students to
groups, so that the groups were as equal as possible on pre-knowledge
scores, this still would not change the fact that students would differ
one from the other in terms of pre-knowledge and this would add "error
variance" in the experiment.

The thing that makes random assignment so powerful is that
greatly decreases systematic error Ė error that varies with the
independent variable. Extraneous variables that vary with the levels of
the independent variable are the most dangerous type in terms of challenging
the validity of experimental results. These types of extraneous variables
have a special name, confounding variables. For example, instead
of randomly assigning students, the instructor may test the new strategy
in the gifted classroom and test the control strategy in a regular class.
Clearly, ability would most likely vary with the levels of the independent
variable. In this case pre-knowledge would become a confounding extraneous
variable. (Animated
illustration of extraneous and confounding variables and systematic vs.
non-systematic error variance.)

One of the most common types of confounding occurs when
an experimenter does not or can not randomly assign participants to groups,
and some type of individual difference (e.g., ability, extroversion, shyness,
height, weight) acts as a confounding variable. For example, any experiment
that involves a comparison of men and women is inherently plagued with
confounding variables, the most commonly cited of which is that the social
environment for males and females is very different. This does not mean
that there is no meaning or value in gender comparison studies, or other
studies in which random assignment is not employed, it simply means that
we need to be more cautious in interpreting the results.

Psychology World was created by Richard
Hall in 1998 and is covered by a creative commons (by-nc) copyright